基于线阵CCD的飞行目标章动角测试技术研究
|
摘要
飞行体的姿态是飞行体理论研究的重要课题,而章动角是飞行体姿态的主要内容之一。章动角的变化是否正常是判断飞行体是否稳定的直接因素,因此,章动角的测试具有重要意义。本文主要解决基于线阵CCD采集图像的章动角测试系统中,图像分析与工程化数据处理中的关键技术问题。
针对飞行体速度高的特点,采用两台高速线阵CCD相机交汇的方法,分别测试两个正交方向的章动角数据,进而获得飞行目标的空间章动角。研究了从图像数据和测试系统参数中获得章动角数据的方法,确定了章动角计算的技术步骤：图像采集、目标分割、飞行目标中心坐标序列提取、飞行目标轴线拟合、尺度对应。分析了线阵CCD采集图像的原理及图像特性,采用差影法分割目标和背景,利用OSTU法计算阈值并分割图像,逐行读取像素值提取目标所在行的坐标值,进而利用平均数法计算目标在各行的中心坐标,采用最小二乘法将这些中心点拟合成轴线,经过尺度对应后,计算章动角的值。
通过对测试原理的研究和深入分析,推导了章动角计算公式,解决了基于CCD图像分析的章动角测试方法工程化中,飞行方向与章动方向的尺度对应问题,从而获得可靠的章动角数据。进一步对章动角计算公式中关键参数的获取方法进行了研究,并详细分析了各参数对测试精度的影响。
用MATLAB7.1软件验证了图像分析与处理算法,借助OPENCV1.0函数库在VC++6.0开发平台下实现了章动角的测试。同时,创建了动态链接库,利用VC++6.0中的MFC将章动角的测试开发成具有可视化界面的软件。
使用帧频为68000f/s的Dalsa-P2-04k40型线阵CCD相机在实验室对气枪弹实际章动角进行测量,经过理论分析,测试精度可达4%。实验表明,本文采用的章动角测试方法可行,测试数据可靠。
Flying objects'posture is an important subject in theoretical research of flying, and nutation angle is one of the main research issues. The status of nutation angel's diversification is a direct factor for judging the stability of the flying object. Therefore, the test of nutation angle is of great significance. The research here focuses on the key technological issues of image analysis and engineering data processing in nutation angle test based on image acquisition by linear CCD.
Due to the high speed of the flying objects, a method of using high rate linear CCD intersection to measure nutation angles of two orthogonal directions is proposed, and the space nutation angel is achieved through the measurement. The method of getting nutation data from image and testing system is studied, and technological steps for calculating nutation angle are identified:image's collection, target's separation, center coordinate's calculation of every line and axis fitting. The principle of linear CCD image collection and characteristics of image are studied; background and target are separated by substation; threshold is obtained by OSTU; target's coordinate is got by reading pixel value line by line; center coordinate of every line is calculated by average method and is fit into axis by least squares method; and nutation angle is calculated after scale corresponds.
The calculation formula is also derived from the research and analysis of testing principle. The problem on the relation between the flying direction and nutation direction is resolved in engineering testing method of nutation angel based on CCD image analysis, and reliable nutation angel data are acquired. Moreover, research on acquisition method of the key parameters in calculation formula is made, and the effect on testing precision is analyzed.
Image analysis and processing algorithms are verified by MATLAB7.1. The test of nutation angle is achieved by VC++6.0 with the help of OPENCV1.0 library. At the same time, a dynamic link library is created, and a visual interface software is developed by the MFC of VC++6.0.
The actual gas cartridges nutation angle is measured in laboratory by linear CCD (Dalsa-P2-04k40) produced from DALSA Company with frame rate 68000. After theoretical analysis, the total nutation angle error is 4%.The test result shows that the nutation angel's testing method is feasible and the data is reliable.
针对飞行体速度高的特点,采用两台高速线阵CCD相机交汇的方法,分别测试两个正交方向的章动角数据,进而获得飞行目标的空间章动角。研究了从图像数据和测试系统参数中获得章动角数据的方法,确定了章动角计算的技术步骤：图像采集、目标分割、飞行目标中心坐标序列提取、飞行目标轴线拟合、尺度对应。分析了线阵CCD采集图像的原理及图像特性,采用差影法分割目标和背景,利用OSTU法计算阈值并分割图像,逐行读取像素值提取目标所在行的坐标值,进而利用平均数法计算目标在各行的中心坐标,采用最小二乘法将这些中心点拟合成轴线,经过尺度对应后,计算章动角的值。
通过对测试原理的研究和深入分析,推导了章动角计算公式,解决了基于CCD图像分析的章动角测试方法工程化中,飞行方向与章动方向的尺度对应问题,从而获得可靠的章动角数据。进一步对章动角计算公式中关键参数的获取方法进行了研究,并详细分析了各参数对测试精度的影响。
用MATLAB7.1软件验证了图像分析与处理算法,借助OPENCV1.0函数库在VC++6.0开发平台下实现了章动角的测试。同时,创建了动态链接库,利用VC++6.0中的MFC将章动角的测试开发成具有可视化界面的软件。
使用帧频为68000f/s的Dalsa-P2-04k40型线阵CCD相机在实验室对气枪弹实际章动角进行测量,经过理论分析,测试精度可达4%。实验表明,本文采用的章动角测试方法可行,测试数据可靠。
Flying objects'posture is an important subject in theoretical research of flying, and nutation angle is one of the main research issues. The status of nutation angel's diversification is a direct factor for judging the stability of the flying object. Therefore, the test of nutation angle is of great significance. The research here focuses on the key technological issues of image analysis and engineering data processing in nutation angle test based on image acquisition by linear CCD.
Due to the high speed of the flying objects, a method of using high rate linear CCD intersection to measure nutation angles of two orthogonal directions is proposed, and the space nutation angel is achieved through the measurement. The method of getting nutation data from image and testing system is studied, and technological steps for calculating nutation angle are identified:image's collection, target's separation, center coordinate's calculation of every line and axis fitting. The principle of linear CCD image collection and characteristics of image are studied; background and target are separated by substation; threshold is obtained by OSTU; target's coordinate is got by reading pixel value line by line; center coordinate of every line is calculated by average method and is fit into axis by least squares method; and nutation angle is calculated after scale corresponds.
The calculation formula is also derived from the research and analysis of testing principle. The problem on the relation between the flying direction and nutation direction is resolved in engineering testing method of nutation angel based on CCD image analysis, and reliable nutation angel data are acquired. Moreover, research on acquisition method of the key parameters in calculation formula is made, and the effect on testing precision is analyzed.
Image analysis and processing algorithms are verified by MATLAB7.1. The test of nutation angle is achieved by VC++6.0 with the help of OPENCV1.0 library. At the same time, a dynamic link library is created, and a visual interface software is developed by the MFC of VC++6.0.
The actual gas cartridges nutation angle is measured in laboratory by linear CCD (Dalsa-P2-04k40) produced from DALSA Company with frame rate 68000. After theoretical analysis, the total nutation angle error is 4%.The test result shows that the nutation angel's testing method is feasible and the data is reliable.
引文
[1]李金珂,陈良益.基于线阵CCD的弹道同步式狭缝摄影系统[J].激光与红外,2009,39(3)：300-303.
[2][EB/OL]http://baike.baidu.com/view/4265652.htm#1
[3]孙照强,李宝柱,鲁耀兵.弹道目标章动特性及其微多普勒研究[J].现代雷达,2009,31(4)：24-27.
[4]刘世平,易文俊.弹丸飞行姿态的计算机采集与处理[J].弹道学报,2001,13(3)：73-77.
[5]高昕,单长胜,李建安,等.弹丸章动周期的光学立靶测量法[J],2003,32(11)：1386-1389.
[6]田园.多目标立靶密集度测试技术研究[D].硕士学位论文,西安工业大学,2010.
[7]Deriche R. Using Canny's criteria to derive an optimal edge detector recursively implemented, Int. [J]. Computer Vision,1987,20(1):167-187.
[8]张林.CCD交汇光靶中的关键技术研究[D].硕士学位论文,安徽大学,2006.
[9]Michael B. Shermana, Jacob Brinka and Wah Chiua. Performance of a slow-scan CCD camera for macromolecular imaging in a 400 kV electron cryomicroscope[J].Elsevier Ltd, 1996,27(2):129-139.
[10]张林.CCD光靶交汇测量技术及应用研究[D].博士学位论文,南京理工大学,2007.
[11]Park J. A.and Y. Lu. Edge detection in grayscale, color, and range images [J]. Computer Science and Engineering,2008,10(2):37-39.
[12]Canny J.A.computational approach to edge detection[J]. IEEE Trans. Pattern Analysis and Machine Intelligence,1986,8(1):679-714.
[13]张玲.弹箭模拟运动姿态的摄影测量研究[D],硕士学位论文,南京理工大学,2008.
[14]Jan T. Bosiers.echnical challenges and recent progress in CCD imagers[J]. Nuclear Instruments and Methods in Physics Research,2006,20(3):148-156.
[15]Barrow H.G. and Tenenbaum J.M. Interpreting line drawings as three-dimensional surfaces[J]. Artificial Intelligence,1981,17(3):75-116.
[16]Paun G,Rozenberg G, Salomaa A.DNA Computing[J].New Computing Paradigms. Springer,1998,20(6):60-63.
[17]王家文.Matlab7.6图形图像处理[M].国防工业出版社,2009.
[18]贾云得.机器视觉[M],北京：科学出版社,2000.
[19]李金珂,陈良益.基于线阵CCD的弹道同步式狭缝摄影系统[J].激光与红外,2009,39(3)：300-303
[20]施浣芳,雷志勇,倪晋平等.高速运动物体飞行参数的CCD测量方法研究[N].西安工业学院学报,2000,20(4)：259-263.
[21]高芬,安莹,倪晋平等.红外测速光幕靶改进及测量精度分析[N].西安工业大学学报,2010,30(3)：205-209.
[22]刘同现,宋卫东,宋不极,等.线阵CCD在弹丸飞行姿态测量中的应用[N].军械工程学院学报,2002,14(3)：23-25.
[23]Geert Verhoeven. Imaging the invisible using modified digital still cameras for straightforward and low-cost archaeological near infrared photography[C], Journal of Archaeological Science.2008,35(12):3087-3100.
[24]高听,王颖,黄惠明.利用线列CCD像机交汇测量弹丸攻角[J].光学技术,2002,28(4)：376-379.
[25]宋寅卯,李晓娟,刘磊.图像噪声滤波的研究方法及进展[J].电脑开发与应用,2010,23(4)：74-76.
[26]姚佳琴,陈琳.数字拍摄中噪波的产生与消除[J].影像技术,2006,1(1)：36-38.
[27][EB/OL]http://baike.baidu.com/view/1307584.htm.
[28]杨华伟.高速线阵CCD光靶信号处理及其固件实现技术研究[D].硕士学位论文,南京理工大学,2007.
[29]李睿.基于红外图像的湖面目标检测算法研究[D].硕士学位论文,河南理工大学,2009.
[30]周敬.图像分割中阈值法的研究[J].机电技术,2010,3(1)：39：42
[31]李强.图像分割中的阈值法研究[N].铜仁职业技术学院学报(自然科学版),2008,6(6)：52-54
[32]王洪.基于遥感图像的月球表面特征分析[D].硕士学位论文,吉林大学,2007.
[33][EB/OL]http://baike.baidu.com/view/60840.htm.
[34]韩晓军.数字图像处理技术与应用[M].电子工业出版社,2009.
[35]Sim K.S. Recursive sub-image histogram equalization applied to gray scale images[M]. Pattern Recognition Letters Encyclopedia of Mathematics, Kluwer/Springer,2007.
[36]阳波.基于最大类间方差遗传算法的图像分割方法[N].湖南师范大学自然科学学报,2003,26(1)：32-36.
[37]罗佳佳.基于差影法与摄相机定标技术的车牌定位研究[D].硕士学位论文,武汉理工大学,2008.
[38]崔凤魁,张丰收,白露等.二值图像目标邻域点法边界跟踪算法[N].洛阳工学院学报,2001,22(1)：28：30.
[39]杨琨,曾立波,王殿成.数学形态学腐蚀膨胀运算的快速算法[J].计算机工程与应用,2005,3(4),54：56.
[40][EB/OL]http://baike.baidu.com/view/1307584.htm.
[41]刘鹏.基于手指静脉网络特征的认证技术研究[D].硕士学位论文,北京交通大学,2009.
[42][EB/OL]http://wenku.baidu.com/view/5bf48802de80d4d8d15a4fal.html最小二乘法拟合原理,百度文库.
[43]刘群华,施浣芳,阎秉先等.红外光幕靶测速系统和精度分析[J].光子学报,2004,33(11)：1409-1411.
[44]苏建刚.天幕靶测速精度分析[J].弹道学报,1994,2(2)：47-53.
[45]IA Hong-tao, ZHU Yuan-chang,WANG Jian-hua. Theprinciple and implementation for extended adaptivemedi-an filter[J]. Journal of Image and Graphics,2004,9(8):948-950.
[46]刘松林,哈长亮,郝向阳.基于机器视觉的线阵CCD相机成像几何模型[N].测绘科学技术学报,2006,23(5)：387-390.
[47]雷玉堂,罗辉,马娟.CCD摄相机的误差及其检校[J].光学与光电技术,2004,2(4)：48-50.
[2][EB/OL]http://baike.baidu.com/view/4265652.htm#1
[3]孙照强,李宝柱,鲁耀兵.弹道目标章动特性及其微多普勒研究[J].现代雷达,2009,31(4)：24-27.
[4]刘世平,易文俊.弹丸飞行姿态的计算机采集与处理[J].弹道学报,2001,13(3)：73-77.
[5]高昕,单长胜,李建安,等.弹丸章动周期的光学立靶测量法[J],2003,32(11)：1386-1389.
[6]田园.多目标立靶密集度测试技术研究[D].硕士学位论文,西安工业大学,2010.
[7]Deriche R. Using Canny's criteria to derive an optimal edge detector recursively implemented, Int. [J]. Computer Vision,1987,20(1):167-187.
[8]张林.CCD交汇光靶中的关键技术研究[D].硕士学位论文,安徽大学,2006.
[9]Michael B. Shermana, Jacob Brinka and Wah Chiua. Performance of a slow-scan CCD camera for macromolecular imaging in a 400 kV electron cryomicroscope[J].Elsevier Ltd, 1996,27(2):129-139.
[10]张林.CCD光靶交汇测量技术及应用研究[D].博士学位论文,南京理工大学,2007.
[11]Park J. A.and Y. Lu. Edge detection in grayscale, color, and range images [J]. Computer Science and Engineering,2008,10(2):37-39.
[12]Canny J.A.computational approach to edge detection[J]. IEEE Trans. Pattern Analysis and Machine Intelligence,1986,8(1):679-714.
[13]张玲.弹箭模拟运动姿态的摄影测量研究[D],硕士学位论文,南京理工大学,2008.
[14]Jan T. Bosiers.echnical challenges and recent progress in CCD imagers[J]. Nuclear Instruments and Methods in Physics Research,2006,20(3):148-156.
[15]Barrow H.G. and Tenenbaum J.M. Interpreting line drawings as three-dimensional surfaces[J]. Artificial Intelligence,1981,17(3):75-116.
[16]Paun G,Rozenberg G, Salomaa A.DNA Computing[J].New Computing Paradigms. Springer,1998,20(6):60-63.
[17]王家文.Matlab7.6图形图像处理[M].国防工业出版社,2009.
[18]贾云得.机器视觉[M],北京：科学出版社,2000.
[19]李金珂,陈良益.基于线阵CCD的弹道同步式狭缝摄影系统[J].激光与红外,2009,39(3)：300-303
[20]施浣芳,雷志勇,倪晋平等.高速运动物体飞行参数的CCD测量方法研究[N].西安工业学院学报,2000,20(4)：259-263.
[21]高芬,安莹,倪晋平等.红外测速光幕靶改进及测量精度分析[N].西安工业大学学报,2010,30(3)：205-209.
[22]刘同现,宋卫东,宋不极,等.线阵CCD在弹丸飞行姿态测量中的应用[N].军械工程学院学报,2002,14(3)：23-25.
[23]Geert Verhoeven. Imaging the invisible using modified digital still cameras for straightforward and low-cost archaeological near infrared photography[C], Journal of Archaeological Science.2008,35(12):3087-3100.
[24]高听,王颖,黄惠明.利用线列CCD像机交汇测量弹丸攻角[J].光学技术,2002,28(4)：376-379.
[25]宋寅卯,李晓娟,刘磊.图像噪声滤波的研究方法及进展[J].电脑开发与应用,2010,23(4)：74-76.
[26]姚佳琴,陈琳.数字拍摄中噪波的产生与消除[J].影像技术,2006,1(1)：36-38.
[27][EB/OL]http://baike.baidu.com/view/1307584.htm.
[28]杨华伟.高速线阵CCD光靶信号处理及其固件实现技术研究[D].硕士学位论文,南京理工大学,2007.
[29]李睿.基于红外图像的湖面目标检测算法研究[D].硕士学位论文,河南理工大学,2009.
[30]周敬.图像分割中阈值法的研究[J].机电技术,2010,3(1)：39：42
[31]李强.图像分割中的阈值法研究[N].铜仁职业技术学院学报(自然科学版),2008,6(6)：52-54
[32]王洪.基于遥感图像的月球表面特征分析[D].硕士学位论文,吉林大学,2007.
[33][EB/OL]http://baike.baidu.com/view/60840.htm.
[34]韩晓军.数字图像处理技术与应用[M].电子工业出版社,2009.
[35]Sim K.S. Recursive sub-image histogram equalization applied to gray scale images[M]. Pattern Recognition Letters Encyclopedia of Mathematics, Kluwer/Springer,2007.
[36]阳波.基于最大类间方差遗传算法的图像分割方法[N].湖南师范大学自然科学学报,2003,26(1)：32-36.
[37]罗佳佳.基于差影法与摄相机定标技术的车牌定位研究[D].硕士学位论文,武汉理工大学,2008.
[38]崔凤魁,张丰收,白露等.二值图像目标邻域点法边界跟踪算法[N].洛阳工学院学报,2001,22(1)：28：30.
[39]杨琨,曾立波,王殿成.数学形态学腐蚀膨胀运算的快速算法[J].计算机工程与应用,2005,3(4),54：56.
[40][EB/OL]http://baike.baidu.com/view/1307584.htm.
[41]刘鹏.基于手指静脉网络特征的认证技术研究[D].硕士学位论文,北京交通大学,2009.
[42][EB/OL]http://wenku.baidu.com/view/5bf48802de80d4d8d15a4fal.html最小二乘法拟合原理,百度文库.
[43]刘群华,施浣芳,阎秉先等.红外光幕靶测速系统和精度分析[J].光子学报,2004,33(11)：1409-1411.
[44]苏建刚.天幕靶测速精度分析[J].弹道学报,1994,2(2)：47-53.
[45]IA Hong-tao, ZHU Yuan-chang,WANG Jian-hua. Theprinciple and implementation for extended adaptivemedi-an filter[J]. Journal of Image and Graphics,2004,9(8):948-950.
[46]刘松林,哈长亮,郝向阳.基于机器视觉的线阵CCD相机成像几何模型[N].测绘科学技术学报,2006,23(5)：387-390.
[47]雷玉堂,罗辉,马娟.CCD摄相机的误差及其检校[J].光学与光电技术,2004,2(4)：48-50.